• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1247-1257
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• 2013

The security vulnerabilities of cloud storage virtualization environments are different from those of the existing computer system and are difficult to be protected in the existing computer system environment. Therefore we need some technical measures to address this issue. First of all, the technology used in cloud storage virtualization environment needs to be thoroughly analyzed, and also, we should understand those security requirements of various stakeholders in the view of cloud storage service and perform the research on security guidelines of the research security requirements. In this paper, we propose security requirements based on layers and roles of cloud storage virtualization. The proposed security requirements can be a basement for development of solution of cloud storage virtualization security.

• Journal of Internet Computing and Services
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• v.17 no.2
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• pp.1-9
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• 2016

Users are provided infrastructure such as CPU, memory, network, and storage as IaaS (Infrastructure as a Service) service on cloud computing environments. However storage instances cannot support the maximum storage capacity that SQL servers can use, because the capacity of instances provided by service providers is usually limited. In this paper, we propose a method of securing mass storage capacity for SQL servers by sharing network disks with limited storage capacity. We confirmed through experiments that it is possible to secure mass storage capacity, which exceeds the maximum storage capacity provided by an instance with Amazon EBS on Amazon EC2 Windows environments, and it is possible to improve the overall performance of the SQL servers by increasing the disk capacity and performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.324-327
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• 2013

Recently, due to evolving cloud computing technology, we can easily and transparently utilize both local computing resource and remote computing resource in real life. Especially, enhancing smart device technologies and network infrastructures promote an increase of needs to share files between local smart devices and cloud storages. However, since smart devices have a limited storage space, storing files on cloud storage causes a starvation problem of local storage. It means that users can face a storage-lack problem even a cloud storage service provide a huge file storing space. In this research, we propose a method to manage files between smart devices and cloud storages. Our approach calculate file usage pattern based on recently used date, and then this approach determines local files being migrated. As a result, our approach is sufficient for handling data synchronization between big data storage farm and local thin client which contains limited storage space.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.277-283
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• 2014

Recently, various cloud service has been being provided on mobile devices as well as desktop pc and server computer. Also, Smartphone users are very rapidly increasing, and they are using it for enjoying various services(cloud service, game, banking service, mobile office, etc.). So, research to utilize resources on mobile device has been conducted. In this paper, We have suggested efficient method of cloud resource management by using information of available physical resources(CPU, memory, storage, etc.) between mobile devices, and information of physical resource in mobile device. Suggested technology is possible to guarantee real-time process and efficiently manage resources.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.363-366
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• 2017

최근 컨텐츠 제공 업체와 사용자들로부터 생성되는 미디어 데이터들의 용량이 늘어남에 따라, 사용자들은 자신이 보유한 단말 외에 추가적인 저장공간이 필요하게 되었다. 이에 추가 저장소 및 백업 장치로써 클라우드 스토리지 서비스의 사용률이 늘어나는 추세이다. 클라우드 서비스에 대한 수요가 증가하고 이와 함께 보안적인 이슈가 늘어남에 따라, 서비스 제공자들은 다양한 보안 기술들을 클라우드 시스템에 적용하고 있다. 본 논문에서는 클라우드 스토리지 서비스의 보안성을 위한 업로드, 다운로드간 파일 암 복호화 방법에 대해 제안한다. 제안한 어플리케이션은 보안 문제들을 해결하는 데에 도움이 될 것으로 기대된다.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.29-36
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• 2016

In cloud storages, as security of stored files and privacy of users become regarded as important concerns, secure cloud storages have been proposed, where stored files are encrypted with file owner's password and even the cloud service provider can not open the file contents. However, if the file owner forgets one's password, one can no longer access the file. To solve this problem, we propose a scheme for changing password for the secure cloud based on proxy re-encryption, which make the file owner enable to change password even when one forgets it. With the proposed scheme, only the file owner can change the password and re-encrypt the files securely because other user and even the service provider can not see the file contents.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.97-103
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• 2020

Linux Cgroups takes a fundamental role for sharing system resources among multiple containers on container-based cloud computing environment. Especially for I/O resource, Linux Cgroups supports a mechanism for sharing I/O bandwidth in proportion to I/O weight. However, the current mechanism of Linux Cgroups using BFQ I/O scheduler seriously degrades the I/O performance with high bandwidth storage device such as NVMe SSDs. In this paper, we proposed a new feedback based I/O bandwidth sharing scheme for Linux Cgroups which allocates I/O credits to containers according to I/O weights and adjusts the amount of credits to performance fluctuation of NVMe SSDs. The proposed scheme is implemented on Linux kernel 5.3 and evaluated. The evaluation results show that it can share the I/O bandwidth among multiple containers proportionally to I/O weights while improving I/O performance more than twice as high as the existing scheme.

• Journal of KIISE
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• v.44 no.8
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• pp.767-773
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• 2017

In a distributed system environment, such as a cloud database, the tail latency needs to be kept short to ensure uniform quality of service. In this paper, through experiments on a Cassandra database, we show that long tail latency is caused by a lack of memory space because the database cannot receive any request until free space is reclaimed by writing the buffered data to the storage device. We observed that, since the performance of the storage device determines the amount of time required for writing the buffered data, the performance degradation of Solid State Drive (SSD) due to garbage collection results in a longer tail latency. We propose a garbage collection synchronization technique, called SyncGC, that simultaneously performs garbage collection in the java virtual machine and in the garbage collection in SSD concurrently, thus hiding garbage collection overheads in the SSD. Our evaluations on real SSDs show that SyncGC reduces the tail latency of $99.9^{th}$ and, $99.9^{th}-percentile$ by 31% and 36%, respectively.

• Journal of Convergence for Information Technology
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• v.8 no.5
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• pp.107-113
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• 2018

With the rapid development of big data and Internet technologies among IT technologies, it is being changed into an environment where data stored in the cloud environment can be used wherever the Internet is connected, without storing important data in an external storage device such as USB. However, protection of users' privacy information is becoming increasingly important as the data being processed in the cloud environment is changed into an environment that can be easily handled. In this paper, we propose a user-reserving management model that can improve the user 's service quality without exposing the information used in the cloud environment to a third party. In the proposed model, user group is grouped into virtual environment so that third party can not handle user's privacy information among data processed in various cloud environments, and then identity property and access control policy are processed by block chain.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.211-216
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• 2021

Information from various heterogeneous devices is steadily increasing in distributed cloud environments. This is because high-speed network speeds and high-capacity multimedia data are being used. However, research is still underway on how to minimize information errors in big data sent and received by heterogeneous devices. In this paper, we propose a deep learning-based asymmetric storage management technique for minimizing bandwidth and data errors in networks generated by information sent and received in cloud environments. The proposed technique applies deep learning techniques to optimize the load balance after asymmetric hash of the big data information generated by each device. The proposed technique is characterized by allowing errors in big data collected from each device, while also ensuring the connectivity of big data by grouping big data into groups of clusters of dogs. In particular, the proposed technique minimizes information errors when storing and managing big data asymmetrically because it used a loss function that extracted similar values between big data as seeds.